Authors
Jaiswal, S., Reddy, M. P., Paul, D., Gandhi, P., Majumder, A.
Abstract
Combination therapies can improve anticancer efficacy, but identifying effective drug pairs and dose combinations requires systematic exploration of multidimensional concentration spaces. Here, we extend a diffusion-driven, flowless microfluidic concentration gradient generator (CGG) to enable quantitative combinatorial drug screening without external pumps or continuous flow. The platform comprises a 5 X 5 array of interconnected culture nodes coupled to four peripheral reservoirs, in which overlapping diffusion fields generate spatially defined single- and multidrug exposures. Computational modelling was used to assign local drug concentrations to individual nodes, enabling direct correlation of the predicted exposure landscape with cellular response. Using MCF-7 breast cancer cells and 5-fluorouracil (5-FU) and doxorubicin (DOX) as model therapeutics, the platform resolved concentration-dependent single-agent responses, yielding IC50 values of 3.46 M for 5-FU and 1.22 M for DOX. Combinatorial loading generated 25 spatially defined 5-FU-DOX concentration pairs within a single device, which were resolved into two-dimensional concentration-response landscapes. Bliss independence analysis revealed concentration-specific drug interactions, with synergy predominating at low-to-intermediate concentrations and a transition towards additive and antagonistic responses at higher exposures. These findings establish a pump-free microfluidic strategy that integrates computational concentration mapping with spatially resolved pharmacological analysis to identify effective drug-combination windows within a single platform.
Preprint server:
bioRxiv
The authors list and abstract were imported from bioRxiv on 11 Sep 2026.
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